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Code implementing a crosscutting concern is often spread over many different parts of an application. Identifying such code automatically greatly improves both the maintainability and the evolvability of the application. First of all, it allows a developer to more easily find the places in the code that must be changed when the concern changes, and thus makes such changes less time consuming and less prone to errors. Second, it allows a developer to refactor the code, so that it uses modern and more advanced abstraction mechanisms, thereby restoring its modularity. In this paper, we evaluate the suitability of clone detection as a technique for the identification of crosscutting concerns. To that end, we manually identify four specific concerns in an industrial C application, and analyze to what extent clone detection is capable of finding these concerns. We consider our results as a stepping stone toward an automated 'concern miner' based on clone detection.

Data contains meteorological and heat flux observations from eddy-covariance towers at 13 sites in different cities.Data is preprocessed for the analysis to infer water storage capacities, which means they are daily aggregates.